Modeling and optimization of electrospun PAN nanofiber diameter using response surface methodology and artificial neural networks

Response surface methodology (RSM) based on a three‐level, three‐variable Box‐Benkhen design (BBD), and artificial neural network (ANN) techniques were compared for modeling the average diameter of electrospun polyacrylonitrile (PAN) nanofibers. The multilayer perceptron (MLP) neural networks were trained by the sets of input–output patterns using a scaled conjugate gradient backpropagation algorithm. The three important electrospinning factors were studied including polymer concentration (w/v%), applied voltage (kV) and the nozzle‐collector distance (cm). The predicted fiber diameters were in agreement with the experimental results in both ANN and RSM techniques. High‐regression coefficient between the variables and the response (R² = 0.998) indicates excellent evaluation of experimental data by second‐order polynomial regression model. The R² value was 0.990, which indicates that the ANN model was shows good fitting with experimental data. Moreover, the RSM model shows much lower absolute percentage error than the ANN model. Therefore, the obtained results indicate that the performance of RSM was better than ANN. The RSM model predicted the 118 nm value of the finest nanofiber diameter at conditions of 10 w/v% polymer concentration, 12 cm of nozzle‐collector distance, and 12 kV of the applied voltage. The predicted value (118 nm) showed only 2.5%, difference with experimental results in which 121 nm at the same setting were observed. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Improved xylitol production in media containing phenolic aldehydes: application of response surface methodology for optimization and modeling of bioprocess

BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2² full‐factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q_P = 0.74 g L^?1h^?1) and yields (Y_P/S = 0.81 g g^?1) can be attained by adding only vanillin at 2.0 g L^?1 to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 ± 0.04 g L^?1 h^?1 and 0.77 ± 0.01 g g^?1) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. Copyright © 2009 Society of Chemical Industry     

Cr(III) removal from simulated solution using hydrous magnesium oxide coated fly ash: Optimization by response surface methodology (RSM)

Hydrous magnesium oxide coated fly ash (MFA) has environmental remediation potential by providing a substrate for the adsorption of aqueous Cr(Ⅲ). Aqueous Cr(Ⅲ) adsorption onto MFA was examined as a function of MFA dosage, pH and initial Cr(Ⅲ) concentration with the Box-Behnken approach used for experimental design and optimization using response surface methodology (RSM). pH and dosage (dosage and concentration) have significant interactive effects on Cr(Ⅲ) adsorption efficiency. Analysis of variance shows that the response surface quadratic model is highly significant and can effectively predict the experimental outcomes. Cr(Ⅲ) removal efficiency of 98% was obtained using optimized conditions of MFA dosage, pH and initial Cr(Ⅲ) concentration of 1.57 g·L^-1, 4.11 and 126 mg·L^-1, respectively. Cr(Ⅲ) adsorption onto MFA is mainly attributed to the interaction between Cr(Ⅲ) and the functional group -OH of the hydrous magnesium oxide, in all probability caused by chemisorptions. The results of this study can conduce to reveal the interactions between Cr(Ⅲ) pollutant and MFA characteristics, posing important implications for the cost-effective alternative adsorption technology in the treatment of heavy metal containing wastewater.     

Experiment research on mix design and early mechanical performance of alkali-activated slag using response surface methodology (RSM)

To enhance the quality of alkali-activated slag (AAS) materials, scientific and efficient mix design method is preferred. This paper presents an optimization of AAS materials using Response Surface Methodology (RSM). Three factors related to early strength such as modulus (n), concentration of alkali activator (CAA) and liquid–solid ratio (LSR) were investigated. Specimens with different mix ratios were prepared based on RSM design. The early mechanical performance was assessed, after 2 or 3 h of curing. Then response surface models were established and the effect law of each factor was systemically analyzed. The result shows that both n and CAA have a significant effect on the early strength, while LSR affects slightly. By adjusting the mix design parameters, the early performance of AAS can be effectively improved. This study verifies that RSM is efficient in the preparation of AAS and it can control the early strength of AAS accurately.     

Optimization of acrylonitrile removal by activated carbon‐granular using response surface methodology

A statistical Box–Behnken design of experiments was performed to evaluate the effects of individual operating variables and their interactions on the acrylonitrile (AN) removal of C₀ = 100 mg/L as fixed input parameter. The variables examined in this study included activated carbon‐granular (AC) dosage, w, temperature, T, and time of contact, t. The significant variables and optimum conditions were identified (w = 4 g/L, T = 30°C, and t = 120 min with AN uptake of 23.97 mg/g of AC) from statistical analysis of the experimental results using response surface methodology (RSM).     

Control of the Fenton process for textile wastewater treatment using artificial neural networks

BACKGROUND: The Fenton process is a popular advanced oxidation process (AOP) for treating textile wastewater. However, high consumption of chemical reagents and high production of sludge are typical problems when using this process and in addition, textile wastewater has wide‐ranging characteristics. Therefore, dynamically regulating the Fenton process is critical to reducing operation costs and enhancing process performance. The artificial neural network (ANN) model has been adopted extensively to optimize wastewater treatment. This study presents a novel Fenton process control strategy using ANN models and oxygen reduction potential (ORP) monitoring to treat two synthetic textile wastewaters containing two common dyes. RESULTS: Experimental results indicated that the ANN models can predict precisely the colour and chemical oxygen demand (COD) removal efficiencies for synthetic textile wastewaters with correlation coefficients (R²) of 0.91–0.99. The proposed control strategy based on these ANN models effectively controls the Fenton process for various effluent colour targets. For treating the RB49 synthetic wastewater to meet the effluent colour targets of 550 and 1500 ADMI units, the required Fe⁺² doses were 13.0–84.3 and 5.5–34.6 mg L^?1 (Fe⁺²/H₂O₂ = 3.0), resulting in average effluent colour values of 520 and 1494 units. On the other hand, an effluent colour target of 550 ADMI units was achieved for RBB synthetic wastewater. The required Fe⁺² doses were 14.6–128.0 mg L^?1; the average effluent colour values were 520 units. CONCLUSION: The Fenton process for textile wastewater treatment was effectively controlled using a control strategy applying the ANN models and ORP monitoring, giving the benefit of chemical cost savings. Copyright © 2009 Society of Chemical Industry     

Polyaniline coated hematite sand supported on graphene oxide (HS@PANI-GO) as a new magnetic material for advanced catalytic oxidation based on sulfate radicals: optimization using response surface methodology

The cover image is based on the Research Article Polyaniline coated hematite sand supported on graphene oxide (HS@PANI-GO) as a new magnetic material for advanced catalytic oxidation based on sulfate radicals: optimization using response surface methodology by Abdellah Ait El Fakir et al., DOI: 10.1002/jctb.6070 .

     

Experimental and modeling study for the removal of formic acid through bulk ionic liquid membrane using response surface methodology

Abstract

In this study, formic acid removal from its aqueous solutions through bulk ionic liquid membrane (BILM) was investigated. Tributyl phosphate (TBP) as a carrier in imidazolium-based ionic liquids was used. D-optimal design based on response surface methodology has been applied to investigate the effect of various operating factors. Initial formic acid concentration, TBP concentration, and NaOH concentration were selected as numerical factors, and ionic liquid type was chosen as a categorical factor. The model equations were obtained to determine BILM process behavior. The removal efficiencies, represented by the extraction and stripping efficiencies, were calculated from the experimental data. The highest removal efficiencies were determined at higher concentration values of TBP and NaOH. All ionic liquids studied in this study had good transport selectivity for the removal of formic acid. The design study showed that BILM is an effective method for the removal of formic acid from the water.     

Modeling, analysis and optimization of aircyclones using artificial neural network, response surface methodology and CFD simulation approaches

The pressure drop is an important performance parameter to evaluate and design cyclone separators. In order to accurately predict the complex non linear relationships between pressure drop and geometrical dimensions, a radial basis neural network (RBFNN) is developed and employed to model the pressure drop for cyclone separators. The neural network has been trained and tested by experimental data available in literature. The result demonstrates that artificial neural networks can offer an alternative and powerful approach to model the cyclone pressure drop. Four mathematical models (Muschelknautz method “MM”, Stairmand, Ramachandran and Shepherd & Lapple) have been tested against the experimental values. The residual error (the difference between the experimental value and the model value) of the MM model is the lowest. The analysis indicates the significant effect of the vortex finder diameter D_x and the vortex finder length S, the inlet width b and the total height H_t. The response surface methodology has been used to fit a second order polynomial to the RBFNN. The second order polynomial has been used to get a new optimized cyclone for minimum pressure drop using the Nelder-Mead optimization technique. A comparison between the new design and the standard Stairmand design has been performed using CFD simulation. CFD results show that the new cyclone design is very close to the Stairmand high efficiency design in the geometrical parameter ratio, and superior for low pressure drop at nearly the same cut-off diameter. The new cyclone design results in nearly 75% of the pressure drop obtained by the old Stairmand design at the same volume flow rate.     

Optimization by response surface methodology (RSM) for toluene adsorption onto prepared acid activated clay

Adsorption of toluene onto acid activated clay was carried out. Modified clay was prepared by acid attack (H₂SO₄) on raw material. Response surface methodology based on a 2‐level, 4‐variables central composite orthogonal design was used to evaluate the effects of important parameters on the adsorption of toluene on to activated clay. Temperature (53.8–96.2°C), contact time (0.57–6.93 h), mass ratio of liquid/solid (3.38–7.62) and strength of acid (7.75–57.24%) were chosen as process variables for the optimization. Of these parameters, temperature reaction and time had greater impact on toluene adsorption than did the other parameters. Analysis of variance (ANOVA) shows a good agreement between theoretical analysis and experimental data. The validity of model is verified by an experiment at the optimum conditions. The optimum conditions for the maximum adsorption of toluene onto activated clay are: temperature of 96.2°C, a contact time of 6.93 h, a liquid/solid ratio of 5.98 and strength of acid of 32.94%. Since the predicted values and the actual experimental value obtained for the maximum adsorption of toluene are within 95% confidence intervals, the final model is considered valid and has satisfactory predictive ability.     

Optimization of biodiesel production from crude palm oil using ultrasonic irradiation assistance and response surface methodology

BACKGROUND: Production of biodiesel from crude palm oil (CPO) with 6 wt% of free fatty acid (FFA) using a low‐frequency ultrasonic irradiation (40 kHz) technique was investigated in the present work. The objective of this study was to determine the relationship between various important parameters of the alkaline catalyzed transesterification process to obtain a high conversion to biodiesel. Response surface methodology (RSM) was used to statistically analyze and optimize the operating parameters of the process. A central composite design (CCD) was adopted to study the effects of the methanol to oil molar ratio, the catalyst concentration, reaction temperature, and irradiation time on conversion to biodiesel. RESULTS: The result from the RSM analysis indicated that the methanol to oil molar ratio, catalyst concentration and irradiation time have the most significant effects on the conversion to biodiesel. Moreover, a coefficient of determination (R²) value of 0.93 shows the fitness of a second‐order model for the present study. Based on this second‐order model, the optimum conditions for alkaline catalyzed transesterification of CPO were found to be a methanol to oil molar ratio of 6.44:1, catalyst concentration 1.25 wt%, reaction temperature 38.44 °C and irradiation time 25.96 min. At the calculated optimum condition, the conversion to biodiesel reached 97.85%. Under these same conditions, the experimental value was 98.02 ± 0.6%. CONCLUSIONS: The mathematical model developed has been proven to adequately describe the range of the experimental parameters studied and provide a statistically accurate prediction of the optimum conversion to biodiesel. Copyright © 2011 Society of Chemical Industry     

Optimization and analysis of nickel adsorption on microwave irradiated rice husk using response surface methodology (RSM)

BACKGROUND: The removal of heavy metals using adsorption techniques with low cost biosorbents is being extensively investigated. The improved adsorption is essentially due to the pores present in the adsorbent. One way of improving the porosity of the material is by irradiation of the precursor using microwaves. In the present study, the adsorption characteristics of nickel onto microwave‐irradiated rice husks were studied and the process variables were optimized through response surface methodology (RSM). RESULT: The adsorption of nickel onto microwave‐irradiated rice husk (MIRH) was found to be better than that of the raw rice husk (RRH). The kinetics of the adsorption of Ni(II) from aqueous solution onto MIRH was found to follow a pseudo‐second‐order model. Thermodynamic parameters such as standard Gibbs free energy (ΔG°), standard enthalpy (ΔH°), and standard entropy (ΔS°) were also evaluated. The thermodynamics of Ni(II) adsorption onto MIRH indicates that it is spontaneous and endothermic in nature. The response surface methodology (RSM) was employed to optimize the design parameters for the present process. CONCLUSION: Microwave‐irradiated rice husk was found to be a suitable adsorbent for the removal of nickel(II) ions from aqueous solutions. The adsorption capacity of the rice husk was found to be 1.17 mg g^?1. The optimized parameters for the current process were found as follows: adsorbent loading 2.8 g (100 mL)^?1; Initial adsorbate concentration 6 mg L^?1; adsorption time 210 min.; and adsorption temperature 35 °C. Copyright © 2008 Society of Chemical Industry     

Optimized reuse and bioconversion from retentate of pre‐filtered palm oil mill effluent (POME) into microbial protease by Aspergillus terreus using response surface methodology

BACKGROUND: The membrane filtration process enables the treatment of wastewater, producing permeate which is less polluted. However, disposal is usually required for the retentate, which is produced as a concentrated constituent along with the permeate. In this study, the authors explored the possibility of reusing, rather than disposing of, the retentate of pre‐filtered palm oil mill effluent (POME) as a fermentation substrate in protease production by a wild type strain of Aspergillus terreus IMI 282743. In addition, the quantitative and interactive effects of the concentration factor for retentate, temperature, inoculum concentration, and fermentation time on the optimization of protease production were investigated using response surface methodology (RSM). RESULTS: Using RSM, the optimum conditions were found to be a concentration factor of 7.27, temperature of 37.95 °C, inoculum concentration of 1.30% (v/v) and fermentation time of 3.83 days. The protease production was increased 4.37‐fold in comparison with the results obtained under non‐optimized conditions. CONCLUSION: To a certain extent, protease production could be enhanced with an increase in concentration factor and temperature, and a decrease of inoculum concentration and fermentation time. Also, POME retentate was found to be a good substrate for protease production with high product activity and without nutrient supplementation. Copyright © 2009 Society of Chemical Industry     

Utilization of response surface methodology to optimize the culture media for the production of rhamnolipids by Pseudomonas aeruginosa AT10

Pseudomonas aeruginosa AT10 produced a mixture of surface‐active rhamnolipids when cultivated on mineral medium with waste free fatty acids as carbon source. The development of the production process to an industrial scale included the design of the culture medium. A 2⁴ full factorial, central composite rotational design and response surface modelling method (RSM) was used to enhance rhamnolipid production by Pseudomonas aeruginosa AT10. The components that are critical for the process medium were the carbon source, the nitrogen source (NaNO₃), the phosphate content (K₂ HPO₄/KH₂PO₄ 2:1) and the iron content (FeSO₄·7H₂O). Two responses were measured, biomass and rhamnolipid production. The maximum biomass obtained was 12.06 g dm^?3 DCW, when the medium contained 50 g dm^?3 carbon source, 9 g dm^?3 NaNO₃, 7 g dm^?3 phosphate and 13.7 mg dm^?3 FeSO₄·7H₂O. The maximum concentration of rhamnolipid, 18.7 g dm^?3, was attained in medium that contained 50 g dm^?3 carbon source, 4.6 g dm^?3 NaNO₃, 1 g dm^?3 phosphate and 7.4 mg dm^?3 FeSO₄·7H₂O. © 2002 Society of Chemical Industry     

Use optimization of natural antioxidants in refined, bleached, and deodorized palm olein during repeated deep-fat frying using response surface methodology

An optimization study on the use of oleoresin rosemary extract, sage extract, and citric acid added into refined, bleached, and deodorized (RBD) palm olein in deep-fat frying of potato chips was carried out using response surface methodology (RSM). Results showed that oleoresin rosemary extract was the most important factor affecting the sensory acceptability of potato chips. For taste and odor, its effects were highly significant (P<0.01), while for crispiness and overall acceptability, the effects were significant (P<0.05). As for sage extract, the level of this antioxidant had a highly significant (P<0.01) effect on appearance and taste and a significant effect (P<0.05) on odor and overall acceptability, but had no effect on crispiness. Although there was no significant synergistic correlation between citric acid and oleoresin rosemary extract or sage extract at the first order, its second order was significantly (P<0.05) related to taste, crispiness, and overall acceptability. An interaction between oleoresin rosemary and sage extracts also significantly (P<0.05) improved the score of overall acceptability of the potato chips. Contour maps of the sensory scores of potato chips indicated that the optimal points for appearance were achieved using 0.062% oleoresin rosemary extract, 0.066% sage extract, and 0.023% citric acid, while optimal task was achieved with 0.063% oleoresin rosemary extract, 0.075% sage extract, and 0.025% citric acid. With the same sequence of ingredients added into oil, the combinations required to achieve the optimal odor, crispiness, and overall acceptability scores were 0.058-0.046-0.026, 0.060-0.071-0.022, and 0.060-0.064-0.026%, respectively.